Author: Toni Krasnic
Publisher: Concise Books Publishing
ISBN: 9780984191406
Category : College student orientation
Languages : en
Pages : 0
Book Description
Explains effective and efficient study methods for students to improve exam and academic performance, describing the author's "Concise Learning Method" (CLM), and featuring thirteen two-page visual maps of essential skills
Concise Learning
How to Study with Mind Maps: The Concise Learning Method for Students and Lifelong Learners
Author:
Publisher: Toni Krasnic
ISBN: 0984191429
Category :
Languages : en
Pages : 160
Book Description
Publisher: Toni Krasnic
ISBN: 0984191429
Category :
Languages : en
Pages : 160
Book Description
Machine Learning
Author: Steven W. Knox
Publisher: John Wiley & Sons
ISBN: 1119439191
Category : Computers
Languages : en
Pages : 357
Book Description
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS PROSE Award Finalist 2019 Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field—presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection— essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning: a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.
Publisher: John Wiley & Sons
ISBN: 1119439191
Category : Computers
Languages : en
Pages : 357
Book Description
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS PROSE Award Finalist 2019 Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field—presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection— essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning: a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.
A Concise Introduction to Machine Learning
Author: A.C. Faul
Publisher: CRC Press
ISBN: 1351204742
Category : Business & Economics
Languages : en
Pages : 335
Book Description
The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise. This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques. The author's webpage for the book can be accessed here.
Publisher: CRC Press
ISBN: 1351204742
Category : Business & Economics
Languages : en
Pages : 335
Book Description
The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise. This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques. The author's webpage for the book can be accessed here.
A Concise Guide to Teaching With Desirable Difficulties
Author: Diane Cummings Persellin
Publisher: Taylor & Francis
ISBN: 1000976882
Category : Education
Languages : en
Pages : 108
Book Description
This concise guidebook on desirable difficulties is designed to be a resource for academics who are interested in engaging students according to the findings of peer-reviewed literature and best practices but do not have the time to immerse themselves in the scholarship of teaching and learning.Intentionally brief, the book is intended to: summarize recent research on five aspects of desirable difficulties; provide applications to the college classroom based on this research; include special sections about teaching strategies that are based on best practices; and offer annotated bibliographies and important citations for faculty who want to pursue additional study. The book will provide a foundation for instructors to teach using evidence-based strategies that will strengthen learning and retention in their classrooms.In addition to chapters on the desirable difficulties, the book also includes chapters on teaching first-year and at-risk students to embrace this approach, on negotiating student resistance, and on using this approach in teaching online.
Publisher: Taylor & Francis
ISBN: 1000976882
Category : Education
Languages : en
Pages : 108
Book Description
This concise guidebook on desirable difficulties is designed to be a resource for academics who are interested in engaging students according to the findings of peer-reviewed literature and best practices but do not have the time to immerse themselves in the scholarship of teaching and learning.Intentionally brief, the book is intended to: summarize recent research on five aspects of desirable difficulties; provide applications to the college classroom based on this research; include special sections about teaching strategies that are based on best practices; and offer annotated bibliographies and important citations for faculty who want to pursue additional study. The book will provide a foundation for instructors to teach using evidence-based strategies that will strengthen learning and retention in their classrooms.In addition to chapters on the desirable difficulties, the book also includes chapters on teaching first-year and at-risk students to embrace this approach, on negotiating student resistance, and on using this approach in teaching online.
Concise Learning and Memory
Author:
Publisher: Academic Press
ISBN: 0080877869
Category : Psychology
Languages : en
Pages : 889
Book Description
The study of learning and memory is a central topic in neuroscience and psychology. Many of the basic research findings are directly applicable in the treatment of diseases and aging phenomena, and have found their way into educational theory and praxis. Concise Learning and Memory represents the best 30 chapters from Learning and Memory: A comprehensive reference (Academic Press March 2008), the most comprehensive source of information about learning and memory ever assembled, selected by one of the most respective scientists in the field, John H. Byrne. This concise version provides a truly authoritative collection of overview articles representing fundamental reviews of our knowledge of this central cognitive function of animal brains. It will be an affordable and accessible reference for scientists and students in all areas of neuroscience and psychology. There is no other single-volume reference with such authority and comprehensive coverage and depth currently available. - Represents an authoritative selection of the fundamental chapters from the most comprehensive source of information about learning and memory ever assembled, Learning and Memory - A comprehensive reference (Academic Press Mar 2008) - Representing outstanding scholarship, each chapter is written by a leader in the field and an expert in the topic area - All topics represent the most up to date research - Full color throughout, heavily illustrated - Priced to provide an affordable reference to individuals and workgroups
Publisher: Academic Press
ISBN: 0080877869
Category : Psychology
Languages : en
Pages : 889
Book Description
The study of learning and memory is a central topic in neuroscience and psychology. Many of the basic research findings are directly applicable in the treatment of diseases and aging phenomena, and have found their way into educational theory and praxis. Concise Learning and Memory represents the best 30 chapters from Learning and Memory: A comprehensive reference (Academic Press March 2008), the most comprehensive source of information about learning and memory ever assembled, selected by one of the most respective scientists in the field, John H. Byrne. This concise version provides a truly authoritative collection of overview articles representing fundamental reviews of our knowledge of this central cognitive function of animal brains. It will be an affordable and accessible reference for scientists and students in all areas of neuroscience and psychology. There is no other single-volume reference with such authority and comprehensive coverage and depth currently available. - Represents an authoritative selection of the fundamental chapters from the most comprehensive source of information about learning and memory ever assembled, Learning and Memory - A comprehensive reference (Academic Press Mar 2008) - Representing outstanding scholarship, each chapter is written by a leader in the field and an expert in the topic area - All topics represent the most up to date research - Full color throughout, heavily illustrated - Priced to provide an affordable reference to individuals and workgroups
Machine Learning Fundamentals
Author: Hui Jiang
Publisher: Cambridge University Press
ISBN: 1108945538
Category : Computers
Languages : en
Pages : 424
Book Description
This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.
Publisher: Cambridge University Press
ISBN: 1108945538
Category : Computers
Languages : en
Pages : 424
Book Description
This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.
A Concise Guide to Improving Student Learning
Author: Diane Cummings Persellin
Publisher: Taylor & Francis
ISBN: 1000976750
Category : Education
Languages : en
Pages : 125
Book Description
This concise guidebook is intended for faculty who are interested in engaging their students and developing deep and lasting learning, but do not have the time to immerse themselves in the scholarship of teaching and learning. Acknowledging the growing body of peer-reviewed literature on practices that can dramatically impact teaching, this intentionally brief book:* Summarizes recent research on six of the most compelling principles in learning and teaching* Describes their application to the college classroom* Presents teaching strategies that are based on pragmatic practices* Provides annotated bibliographies and important citations for faculty who want to explore these topics further This guidebook begins with an overview of how we learn, covering such topics such as the distinction between expert and novice learners, memory, prior learning, and metacognition. The body of the book is divided into three main sections each of which includes teaching principles, applications, and related strategies – most of which can be implemented without extensive preparation.The applications sections present examples of practice across a diverse range of disciplines including the sciences, humanities, arts, and pre-professional programs. This book provides a foundation for the reader explore these approaches and methods in his or her teaching.
Publisher: Taylor & Francis
ISBN: 1000976750
Category : Education
Languages : en
Pages : 125
Book Description
This concise guidebook is intended for faculty who are interested in engaging their students and developing deep and lasting learning, but do not have the time to immerse themselves in the scholarship of teaching and learning. Acknowledging the growing body of peer-reviewed literature on practices that can dramatically impact teaching, this intentionally brief book:* Summarizes recent research on six of the most compelling principles in learning and teaching* Describes their application to the college classroom* Presents teaching strategies that are based on pragmatic practices* Provides annotated bibliographies and important citations for faculty who want to explore these topics further This guidebook begins with an overview of how we learn, covering such topics such as the distinction between expert and novice learners, memory, prior learning, and metacognition. The body of the book is divided into three main sections each of which includes teaching principles, applications, and related strategies – most of which can be implemented without extensive preparation.The applications sections present examples of practice across a diverse range of disciplines including the sciences, humanities, arts, and pre-professional programs. This book provides a foundation for the reader explore these approaches and methods in his or her teaching.
Learning by Doing
Author: Richard DuFour
Publisher: Solution Tree Press
ISBN: 1935249894
Category : Education
Languages : en
Pages : 318
Book Description
Like the first edition, the second edition of Learning by Doing: A Handbook for Professional Learning Communities at Work helps educators close the knowing-doing gap as they transform their schools into professional learning communities (PLCs).
Publisher: Solution Tree Press
ISBN: 1935249894
Category : Education
Languages : en
Pages : 318
Book Description
Like the first edition, the second edition of Learning by Doing: A Handbook for Professional Learning Communities at Work helps educators close the knowing-doing gap as they transform their schools into professional learning communities (PLCs).
Learning Online
Author: George Veletsianos
Publisher: JHU Press
ISBN: 1421438100
Category : Education
Languages : en
Pages : 185
Book Description
What's it really like to learn online?Learning Online: The Student Experience Online learning is ubiquitous for millions of students worldwide, yet our understanding of student experiences in online learning settings is limited. The geographic distance that separates faculty from students in an online environment is its signature feature, but it is also one that risks widening the gulf between teachers and learners. In Learning Online, George Veletsianos argues that in order to critique, understand, and improve online learning, we must examine it through the lens of student experience. Approaching the topic with stories that elicit empathy, compassion, and care, Veletsianos relays the diverse day-to-day experiences of online learners. Each in-depth chapter follows a single learner's experience while focusing on an important or noteworthy aspect of online learning, tackling everything from demographics, attrition, motivation, and loneliness to cheating, openness, flexibility, social media, and digital divides. Veletsianos also draws on these case studies to offer recommendations for the future and lessons learned. The elusive nature of online learners' experiences, the book reveals, is a problem because it prevents us from doing better: from designing more effective online courses, from making evidence-informed decisions about online education, and from coming to our work with the full sense of empathy that our students deserve. Writing in an evocative, accessible, and concise manner, Veletsianos concretely demonstrates why it is so important to pay closer attention to the stories of students—who may have instructive and insightful ideas about the future of education.
Publisher: JHU Press
ISBN: 1421438100
Category : Education
Languages : en
Pages : 185
Book Description
What's it really like to learn online?Learning Online: The Student Experience Online learning is ubiquitous for millions of students worldwide, yet our understanding of student experiences in online learning settings is limited. The geographic distance that separates faculty from students in an online environment is its signature feature, but it is also one that risks widening the gulf between teachers and learners. In Learning Online, George Veletsianos argues that in order to critique, understand, and improve online learning, we must examine it through the lens of student experience. Approaching the topic with stories that elicit empathy, compassion, and care, Veletsianos relays the diverse day-to-day experiences of online learners. Each in-depth chapter follows a single learner's experience while focusing on an important or noteworthy aspect of online learning, tackling everything from demographics, attrition, motivation, and loneliness to cheating, openness, flexibility, social media, and digital divides. Veletsianos also draws on these case studies to offer recommendations for the future and lessons learned. The elusive nature of online learners' experiences, the book reveals, is a problem because it prevents us from doing better: from designing more effective online courses, from making evidence-informed decisions about online education, and from coming to our work with the full sense of empathy that our students deserve. Writing in an evocative, accessible, and concise manner, Veletsianos concretely demonstrates why it is so important to pay closer attention to the stories of students—who may have instructive and insightful ideas about the future of education.